# -*- coding: utf-8 -*-
"""
Module for handling dynamic mesh updates.

This module implements the dynamic meshing strategy described in the report,
which includes rigid body motion for the inner zone and spring-based smoothing
for the deforming outer zone.
"""
import numpy as np
import logging

from .mesh import Mesh
from .kinematics import WingKinematics

class DynamicMeshManager:
    """
    Manages the updates to the mesh at each time step.
    """
    def __init__(self, mesh: Mesh, kinematics: WingKinematics, config):
        """
        Initializes the DynamicMeshManager.

        Args:
            mesh (Mesh): The computational mesh object.
            kinematics (WingKinematics): The wing kinematics calculator.
            config: The simulation configuration object.
        """
        self.mesh = mesh
        self.kinematics = kinematics
        self.config = config
        
        # Store the initial positions of all points for reference
        self.initial_points = np.copy(self.mesh.points)
        self.previous_points = np.copy(self.mesh.points)

        # The axis of rotation for the wing (e.g., the body's edge)
        # This is often the origin if the wing is modeled at (0,0,0)
        self.rotation_axis_origin = np.array([0.0, 0.0, 0.0])

    def update(self, t: float):
        """
        Updates the entire mesh for the current time step.

        Args:
            t (float): The current simulation time.
        """
        logging.debug(f"Updating mesh for time t={t:.4f}s")
        
        # 1. Apply rigid body motion to the wing and inner zone
        self._apply_rigid_body_motion(t)

        # 2. Deform the outer zone using spring-based smoothing
        self._apply_spring_based_smoothing()

        # 3. (Placeholder) Check mesh quality and perform local remeshing if needed
        self._check_and_remesh()
        
        # Update the previous points for the next iteration
        self.previous_points = np.copy(self.mesh.points)

    def _apply_rigid_body_motion(self, t: float):
        """
        Applies solid body rotation to the nodes in the rigid zone.
        """
        # In this framework, we assume the wing itself defines the rigid motion.
        # If there were a separate 'inner zone', its nodes would be moved here too.
        
        wing_node_indices = self.mesh.wing_nodes
        if wing_node_indices is None or wing_node_indices.size == 0:
            logging.warning("No wing nodes identified. Skipping rigid body motion.")
            return

        # Get the rotation matrix for the current time
        R_t = self.kinematics.get_rotation_matrix(t)
        
        # Get the initial positions of the wing nodes
        initial_wing_points = self.initial_points[wing_node_indices]
        
        # Apply rotation
        # Note: This assumes the wing rotates around the origin. If the hinge is
        # elsewhere, a translation to the origin, rotation, and translation back
        # would be needed.
        new_wing_points = (R_t @ (initial_wing_points - self.rotation_axis_origin).T).T \
                          + self.rotation_axis_origin

        # Update the mesh points
        self.mesh.points[wing_node_indices] = new_wing_points
        logging.debug(f"Applied rigid motion to {len(wing_node_indices)} wing nodes.")

    def _apply_spring_based_smoothing(self):
        """
        Deforms the unstructured outer zone using a spring-based analogy.
        
        This is a simplified implementation. Production solvers use more complex
        and optimized versions of this algorithm.
        """
        deforming_nodes = self.mesh.deforming_zone_nodes
        if deforming_nodes.size == 0:
            logging.debug("No deforming nodes to smooth.")
            return

        # This is a highly simplified placeholder. A real implementation is complex:
        # - It requires the mesh connectivity (adjacency list of nodes).
        # - It's an iterative process that solves for node displacements.
        # - The displacement of a node is the weighted average of its neighbors' displacements.
        #
        # The equation is: d_i = (sum(k_ij * d_j)) / sum(k_ij)
        # where d_i is displacement of node i, d_j is displacement of neighbor j,
        # and k_ij is the "spring stiffness" (e.g., 1 / distance).
        
        logging.debug("Spring-based smoothing is a placeholder. No mesh deformation is being calculated.")
        # To show some effect, we can implement a trivial diffusion of displacement from
        # the boundary, but this is not physically accurate spring-smoothing.
        
        # The logic below is NOT a real spring-based smoother but serves to illustrate
        # where such logic would go. A proper implementation would require iterating
        # until displacements converge.
        
        boundary_displacements = self.mesh.points - self.previous_points
        
        # A real implementation would diffuse these displacements inwards through the
        # deforming zone.

    def _check_and_remesh(self):
        """
        (Placeholder) Checks mesh quality and triggers local remeshing.
        
        In a real solver, this would:
        1. Iterate through all cells in the deforming zone.
        2. Calculate a quality metric for each cell (e.g., skewness, aspect ratio).
        3. If the quality of a cell is below a threshold (from config.MAX_CELL_SKEWNESS),
           add it to a "bad cells" list.
        4. If the list is not empty, identify the region of cells around the bad cells.
        5. Delete the cells in that region, creating a "hole" in the mesh.
        6. Call an external meshing library (like a Python binding to GMSH or TetGen)
           to remesh the hole.
        7. Update the mesh data structures with the new nodes and cells.
        """
        logging.debug("Checking mesh quality (placeholder)...")
        # This function would be highly complex to implement.
        pass 